Energy harvesting from solar sources in an attempt to increase efficiency has sparked interest in many communities to develop more energy harvesting applications for renewable energy topics. Advanced technical methods are required to ensure the maximum available power is harnessed from the photovoltaic (PV) system. This dissertation proposed a new discrete-in-time extremum-seeking (ES) based technique for tracking the maximum power point of a photovoltaic array. The proposed method is a true maximum power point tracker that can be implemented with reasonable processing effort on an expensive digital controller. The dissertation presented a stability analysis of the proposed method to guarantee the convergence of the algorithm.

Two-types of PV systems were designed and comprehensive framework of control design was considered for a stand-alone and a three-phase grid connected system. Grid-tied systems commonly have a two-stage power electronics interface, which is necessary due to the inherent limitation of the DC-AC (Inverter) power converging stage. However, a one stage converter topology, denoted as Quasi-Z-source inverter (q-ZSI), was selected to interface the PV panel which overcomes the inverter limitations to harvest the maximum available power.

A powerful control scheme called Model Predictive Control with Finite Set (MPC-FS) was designed to control the grid connected system. The predictive control was selected to achieve a robust controller with superior dynamic response in conjunction with the extremum-seeking algorithm to enhance the system behavior. The proposed method exhibited a better performance in comparison to conventional Maximum Power Point Tracking (MPPT) methods and required less computational effort than the complex mathematical methods.